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Hanalioglu S, Bahadir S, Ozak AC, Yangi K, Mignucci-Jiménez G, Gurses ME, Fuentes A, Mathew E, Graham DT, Altug MY, Gok E, Turner GH, Lawton MT, Preul MC. Ultrahigh-resolution 7-Tesla anatomic magnetic resonance imaging and diffusion tensor imaging of ex vivo formalin-fixed human brainstem-cerebellum complex. Front Hum Neurosci 2024; 18:1484431. [PMID: 39664682 PMCID: PMC11631901 DOI: 10.3389/fnhum.2024.1484431] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2024] [Accepted: 11/04/2024] [Indexed: 12/13/2024] Open
Abstract
Introduction Brain cross-sectional images, tractography, and segmentation are valuable resources for neuroanatomical education and research but are also crucial for neurosurgical planning that may improve outcomes in cerebellar and brainstem interventions. Although ultrahigh-resolution 7-Tesla (7T) magnetic resonance imaging (MRI) and diffusion tensor imaging (DTI) reveal such structural brain details in living or fresh unpreserved brain tissue, imaging standard formalin-preserved cadaveric brain specimens often used for neurosurgical anatomic studies has proven difficult. This study sought to develop a practical protocol to provide anatomic information and tractography results of an ex vivo human brainstem-cerebellum specimen. Materials and methods A protocol was developed for specimen preparation and 7T MRI with image postprocessing on a combined brainstem-cerebellum specimen obtained from an 85-year-old male cadaver with a postmortem interval of 1 week that was stored in formalin for 6 months. Anatomic image series were acquired for detailed views and diffusion tractography to map neural pathways and segment major anatomic structures within the brainstem and cerebellum. Results Complex white matter tracts were visualized with high-precision segmentation of crucial brainstem structures, delineating the brainstem-cerebellum and mesencephalic-dentate connectivity, including the Guillain-Mollaret triangle. Tractography and fractional anisotropy mapping revealed the complexities of white matter fiber pathways, including the superior, middle, and inferior cerebellar peduncles and visible decussating fibers. 3-dimensional (3D) reconstruction and quantitative and qualitative analyses verified the anatomical precision of the imaging relative to a standard brain space. Discussion This novel imaging protocol successfully captured the intricate 3D architecture of the brainstem-cerebellum network. The protocol, unique in several respects (including tissue preservation and rehydration times, choice of solutions, preferred sequences, voxel sizes, and diffusion directions) aimed to balance high resolution and practical scan times. This approach provided detailed neuroanatomical imaging while avoiding impractically long scan times. The extended postmortem and fixation intervals did not compromise the diffusion imaging quality. Moreover, the combination of time efficiency and ultrahigh-resolution imaging results makes this protocol a strong candidate for optimal use in detailed neuroanatomical studies, particularly in presurgical trajectory planning.
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Affiliation(s)
- Sahin Hanalioglu
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
- Department of Neurosurgery, Hacettepe University, Ankara, Türkiye
| | - Siyar Bahadir
- Department of Neurosurgery, Hacettepe University, Ankara, Türkiye
| | - Ahmet C. Ozak
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
- Department of Neurosurgery, Akdeniz University, Antalya, Türkiye
| | - Kivanc Yangi
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
- Department of Neurosurgery, Turkish Republic Ministry of Health, University of Health Sciences, Prof. Dr. Cemil Tascioglu City Hospital, Istanbul, Türkiye
| | - Giancarlo Mignucci-Jiménez
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
| | - Muhammet Enes Gurses
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
| | - Alberto Fuentes
- Neuroimaging Innovation Center, St. Joseph's Hospital and Medical Center, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Ethan Mathew
- Neuroimaging Innovation Center, St. Joseph's Hospital and Medical Center, Barrow Neurological Institute, Phoenix, AZ, United States
| | - Dakota T. Graham
- Thurston Innovation Center, St. Joseph's Hospital and Medical Center, Barrow Neurological Institute, Phoenix, AZ, United States
| | | | - Egemen Gok
- Department of Neurosurgery, Hacettepe University, Ankara, Türkiye
| | - Gregory H. Turner
- Center for In Vivo Imaging and Therapeutics, St. Jude Children's Research Hospital, Memphis, TN, United States
| | - Michael T. Lawton
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
| | - Mark C. Preul
- The Loyal and Edith Davis Neurosurgical Research Laboratory, Department of Neurosurgery, Barrow Neurological Institute, St. Joseph's Hospital and Medical Center, Phoenix, AZ, United States
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Alkemade A, Großmann R, Bazin PL, Forstmann BU. Mixed methodology in human brain research: integrating MRI and histology. Brain Struct Funct 2023; 228:1399-1410. [PMID: 37365411 PMCID: PMC10335951 DOI: 10.1007/s00429-023-02675-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/26/2023] [Accepted: 06/20/2023] [Indexed: 06/28/2023]
Abstract
Postmortem magnetic resonance imaging (MRI) can provide a bridge between histological observations and the in vivo anatomy of the human brain. Approaches aimed at the co-registration of data derived from the two techniques are gaining interest. Optimal integration of the two research fields requires detailed knowledge of the tissue property requirements for individual research techniques, as well as a detailed understanding of the consequences of tissue fixation steps on the imaging quality outcomes for both MRI and histology. Here, we provide an overview of existing studies that bridge between state-of-the-art imaging modalities, and discuss the background knowledge incorporated into the design, execution and interpretation of postmortem studies. A subset of the discussed challenges transfer to animal studies as well. This insight can contribute to furthering our understanding of the normal and diseased human brain, and to facilitate discussions between researchers from the individual disciplines.
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Affiliation(s)
- Anneke Alkemade
- Integrative Model-Based Cognitive Neuroscience Unit, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands.
| | - Rosa Großmann
- Integrative Model-Based Cognitive Neuroscience Unit, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
| | - Pierre-Louis Bazin
- Integrative Model-Based Cognitive Neuroscience Unit, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
- Department of Neurology, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany
| | - Birte U Forstmann
- Integrative Model-Based Cognitive Neuroscience Unit, Department of Psychology, University of Amsterdam, Amsterdam, The Netherlands
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Ivanov D, De Martino F, Formisano E, Fritz FJ, Goebel R, Huber L, Kashyap S, Kemper VG, Kurban D, Roebroeck A, Sengupta S, Sorger B, Tse DHY, Uludağ K, Wiggins CJ, Poser BA. Magnetic resonance imaging at 9.4 T: the Maastricht journey. MAGMA (NEW YORK, N.Y.) 2023; 36:159-173. [PMID: 37081247 PMCID: PMC10140139 DOI: 10.1007/s10334-023-01080-4] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/29/2022] [Revised: 03/18/2023] [Accepted: 03/20/2023] [Indexed: 04/22/2023]
Abstract
The 9.4 T scanner in Maastricht is a whole-body magnet with head gradients and parallel RF transmit capability. At the time of the design, it was conceptualized to be one of the best fMRI scanners in the world, but it has also been used for anatomical and diffusion imaging. 9.4 T offers increases in sensitivity and contrast, but the technical ultra-high field (UHF) challenges, such as field inhomogeneities and constraints set by RF power deposition, are exacerbated compared to 7 T. This article reviews some of the 9.4 T work done in Maastricht. Functional imaging experiments included blood oxygenation level-dependent (BOLD) and blood-volume weighted (VASO) fMRI using different readouts. BOLD benefits from shorter T2* at 9.4 T while VASO from longer T1. We show examples of both ex vivo and in vivo anatomical imaging. For many applications, pTx and optimized coils are essential to harness the full potential of 9.4 T. Our experience shows that, while considerable effort was required compared to our 7 T scanner, we could obtain high-quality anatomical and functional data, which illustrates the potential of MR acquisitions at even higher field strengths. The practical challenges of working with a relatively unique system are also discussed.
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Affiliation(s)
- Dimo Ivanov
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands.
| | - Federico De Martino
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Elia Formisano
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Francisco J Fritz
- Institute of Systems Neuroscience, Center for Experimental Medicine, University Medical Center Hamburg-Eppendorf (UKE), Hamburg, Germany
| | - Rainer Goebel
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Laurentius Huber
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Sriranga Kashyap
- Krembil Brain Institute, University Health Network, Toronto, ON, Canada
| | - Valentin G Kemper
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Denizhan Kurban
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Alard Roebroeck
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | | | - Bettina Sorger
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
| | - Desmond H Y Tse
- Scannexus BV, Oxfordlaan 55, 6229 EV, Maastricht, The Netherlands
| | - Kâmil Uludağ
- Krembil Brain Institute, Koerner Scientist in MR Imaging, University Health Network Toronto, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Center for Neuroscience Imaging Research, Institute for Basic Science and Department of Biomedical Engineering, Sungkyunkwan University, Suwon, Republic of Korea
| | - Christopher J Wiggins
- Imaging Core Facility (INM-ICF), Institut für Neurowissenschaften und Medizin, Forschungszentrum Jülich GmbH, 52425, Jülich, Germany
| | - Benedikt A Poser
- Faculty of Psychology and Neuroscience, Maastricht University, Universiteitssingel 40, 6229 ER, Maastricht, The Netherlands
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Ramos-Llordén G, Lobos RA, Kim TH, Tian Q, Witzel T, Lee HH, Scholz A, Keil B, Yendiki A, Bilgiç B, Haldar JP, Huang SY. High-fidelity, high-spatial-resolution diffusion magnetic resonance imaging of ex vivo whole human brain at ultra-high gradient strength with structured low-rank echo-planar imaging ghost correction. NMR IN BIOMEDICINE 2023; 36:e4831. [PMID: 36106429 PMCID: PMC9883835 DOI: 10.1002/nbm.4831] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/08/2022] [Revised: 08/20/2022] [Accepted: 09/11/2022] [Indexed: 06/15/2023]
Abstract
Diffusion magnetic resonance imaging (dMRI) of whole ex vivo human brain specimens enables three-dimensional (3D) mapping of structural connectivity at the mesoscopic scale, providing detailed evaluation of fiber architecture and tissue microstructure at a spatial resolution that is difficult to access in vivo. To account for the short T2 and low diffusivity of fixed tissue, ex vivo dMRI is often acquired using strong diffusion-sensitizing gradients and multishot/segmented 3D echo-planar imaging (EPI) sequences to achieve high spatial resolution. However, the combination of strong diffusion-sensitizing gradients and multishot/segmented EPI readout can result in pronounced ghosting artifacts incurred by nonlinear spatiotemporal variations in the magnetic field produced by eddy currents. Such ghosting artifacts cannot be corrected with conventional correction solutions and pose a significant roadblock to leveraging human MRI scanners with ultrahigh gradients for ex vivo whole-brain dMRI. Here, we show that ghosting-correction approaches that correct for either polarity-related ghosting or shot-to-shot variations in a separate manner are suboptimal for 3D multishot diffusion-weighted EPI experiments in fixed human brain specimens using strong diffusion-sensitizing gradients on the 3-T Connectom MRI scanner, resulting in orientationally biased dMRI estimates. We apply a recently developed advanced k-space reconstruction method based on structured low-rank matrix (SLM) modeling that handles both polarity-related ghosting and shot-to-shot variation simultaneously, to mitigate artifacts in high-angular resolution multishot dMRI data acquired in several fixed human brain specimens at 0.7-0.8-mm isotropic spatial resolution using b-values up to 10,000 s/mm2 and gradient strengths up to 280 mT/m. We demonstrate the improved mapping of diffusion tensor imaging and fiber orientation distribution functions in key neuroanatomical areas distributed across the whole brain using SLM-based EPI ghost correction compared with alternative techniques.
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Affiliation(s)
- Gabriel Ramos-Llordén
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Rodrigo A. Lobos
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA
| | - Tae Hyung Kim
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Computer Engineering, Hongik University, Seoul, Republic of Korea
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | | | - Hong-Hsi Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Alina Scholz
- Institute of Medical Physics and Radiation Protection, Mittelhessen University of Applied Sciences, Giessen, Germany
| | - Boris Keil
- Institute of Medical Physics and Radiation Protection, Mittelhessen University of Applied Sciences, Giessen, Germany
- Department of Diagnostic and Interventional Radiology, University Hospital Marburg, Philipps University of Marburg, Marburg, Germany
| | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
| | - Berkin Bilgiç
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Justin P. Haldar
- Ming Hsieh Department of Electrical and Computer Engineering, University of Southern California, Los Angeles, California, USA
| | - Susie Y. Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, Massachusetts, USA
- Department of Radiology, Harvard Medical School, Boston, Massachusetts, USA
- Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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5
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Axer M, Amunts K. Scale matters: The nested human connectome. Science 2022; 378:500-504. [DOI: 10.1126/science.abq2599] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Abstract
A comprehensive description of how neurons and entire brain regions are interconnected is fundamental for a mechanistic understanding of brain function and dysfunction. Neuroimaging has shaped the way to approaching the human brain’s connectivity on the basis of diffusion magnetic resonance imaging and tractography. At the same time, polarization, fluorescence, and electron microscopy became available, which pushed spatial resolution and sensitivity to the axonal or even to the synaptic level. New methods are mandatory to inform and constrain whole-brain tractography by regional, high-resolution connectivity data and local fiber geometry. Machine learning and simulation can provide predictions where experimental data are missing. Future interoperable atlases require new concepts, including high-resolution templates and directionality, to represent variants of tractography solutions and estimates of their accuracy.
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Affiliation(s)
- Markus Axer
- Institute of Neurosciences and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Department of Physics, School of Mathematics and Natural Sciences, Bergische Universität Wuppertal, Wuppertal, Germany
| | - Katrin Amunts
- Institute of Neurosciences and Medicine (INM-1), Research Centre Jülich, Jülich, Germany
- Cécile and Oskar Vogt Institute for Brain Research, Medical Faculty, University Hospital Düsseldorf, Heinrich-Heine University Düsseldorf, Düsseldorf, Germany
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6
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Yendiki A, Aggarwal M, Axer M, Howard AF, van Cappellen van Walsum AM, Haber SN. Post mortem mapping of connectional anatomy for the validation of diffusion MRI. Neuroimage 2022; 256:119146. [PMID: 35346838 PMCID: PMC9832921 DOI: 10.1016/j.neuroimage.2022.119146] [Citation(s) in RCA: 44] [Impact Index Per Article: 22.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/16/2021] [Revised: 03/02/2022] [Accepted: 03/23/2022] [Indexed: 01/13/2023] Open
Abstract
Diffusion MRI (dMRI) is a unique tool for the study of brain circuitry, as it allows us to image both the macroscopic trajectories and the microstructural properties of axon bundles in vivo. The Human Connectome Project ushered in an era of impressive advances in dMRI acquisition and analysis. As a result of these efforts, the quality of dMRI data that could be acquired in vivo improved substantially, and large collections of such data became widely available. Despite this progress, the main limitation of dMRI remains: it does not image axons directly, but only provides indirect measurements based on the diffusion of water molecules. Thus, it must be validated by methods that allow direct visualization of axons but that can only be performed in post mortem brain tissue. In this review, we discuss methods for validating the various features of connectional anatomy that are extracted from dMRI, both at the macro-scale (trajectories of axon bundles), and at micro-scale (axonal orientations and other microstructural properties). We present a range of validation tools, including anatomic tracer studies, Klingler's dissection, myelin stains, label-free optical imaging techniques, and others. We provide an overview of the basic principles of each technique, its limitations, and what it has taught us so far about the accuracy of different dMRI acquisition and analysis approaches.
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Affiliation(s)
- Anastasia Yendiki
- Department of Radiology, Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Charlestown, MA, United States,Corresponding author (A. Yendiki)
| | - Manisha Aggarwal
- Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, MD, United States
| | - Markus Axer
- Forschungszentrum Jülich, Institute of Neuroscience and Medicine, Jülich, Germany,Department of Physics, University of Wuppertal Germany
| | - Amy F.D. Howard
- Wellcome Centre for Integrative Neuroimaging, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, United Kingdom
| | - Anne-Marie van Cappellen van Walsum
- Department of Medical Imaging, Anatomy, Radboud University Medical Center, Nijmegen, the Netherland,Cognition and Behaviour, Donders Institute for Brain, Nijmegen, the Netherland
| | - Suzanne N. Haber
- Department of Pharmacology and Physiology, University of Rochester, Rochester, NY, United States,McLean Hospital, Belmont, MA, United States
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Grier MD, Yacoub E, Adriany G, Lagore RL, Harel N, Zhang RY, Lenglet C, Uğurbil K, Zimmermann J, Heilbronner SR. Ultra-high field (10.5T) diffusion-weighted MRI of the macaque brain. Neuroimage 2022; 255:119200. [PMID: 35427769 PMCID: PMC9446284 DOI: 10.1016/j.neuroimage.2022.119200] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Revised: 03/08/2022] [Accepted: 04/07/2022] [Indexed: 11/26/2022] Open
Abstract
Diffu0sion-weighted magnetic resonance imaging (dMRI) is a non-invasive imaging technique that provides information about the barriers to the diffusion of water molecules in tissue. In the brain, this information can be used in several important ways, including to examine tissue abnormalities associated with brain disorders and to infer anatomical connectivity and the organization of white matter bundles through the use of tractography algorithms. However, dMRI also presents certain challenges. For example, historically, the biological validation of tractography models has shown only moderate correlations with anatomical connectivity as determined through invasive tract-tracing studies. Some of the factors contributing to such issues are low spatial resolution, low signal-to-noise ratios, and long scan times required for high-quality data, along with modeling challenges like complex fiber crossing patterns. Leveraging the capabilities provided by an ultra-high field scanner combined with denoising, we have acquired whole-brain, 0.58 mm isotropic resolution dMRI with a 2D-single shot echo planar imaging sequence on a 10.5 Tesla scanner in anesthetized macaques. These data produced high-quality tractograms and maps of scalar diffusion metrics in white matter. This work demonstrates the feasibility and motivation for in-vivo dMRI studies seeking to benefit from ultra-high fields.
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Affiliation(s)
- Mark D Grier
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States
| | - Essa Yacoub
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Gregor Adriany
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Russell L Lagore
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Noam Harel
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Department of Neurosurgery, University of Minnesota, Minneapolis, MN 55455, United States
| | - Ru-Yuan Zhang
- Institute of Psychology and Behavioral Science, Shanghai Jiao Tong University, Shanghai 200030, P.R. China; Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai 200030, P.R. China; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Christophe Lenglet
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States
| | - Kâmil Uğurbil
- Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Jan Zimmermann
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States; Center for Magnetic Resonance Research, Department of Radiology, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States; Department of Biomedical Engineering, University of Minnesota, Minneapolis, MN 55455, United States
| | - Sarah R Heilbronner
- Department of Neuroscience, University of Minnesota, Minneapolis, MN 55455, United States; Center for Neuroengineering, University of Minnesota, Minneapolis, MN 55455, United States.
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8
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Fan Q, Eichner C, Afzali M, Mueller L, Tax CMW, Davids M, Mahmutovic M, Keil B, Bilgic B, Setsompop K, Lee HH, Tian Q, Maffei C, Ramos-Llordén G, Nummenmaa A, Witzel T, Yendiki A, Song YQ, Huang CC, Lin CP, Weiskopf N, Anwander A, Jones DK, Rosen BR, Wald LL, Huang SY. Mapping the human connectome using diffusion MRI at 300 mT/m gradient strength: Methodological advances and scientific impact. Neuroimage 2022; 254:118958. [PMID: 35217204 PMCID: PMC9121330 DOI: 10.1016/j.neuroimage.2022.118958] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 01/27/2022] [Accepted: 01/31/2022] [Indexed: 12/20/2022] Open
Abstract
Tremendous efforts have been made in the last decade to advance cutting-edge MRI technology in pursuit of mapping structural connectivity in the living human brain with unprecedented sensitivity and speed. The first Connectom 3T MRI scanner equipped with a 300 mT/m whole-body gradient system was installed at the Massachusetts General Hospital in 2011 and was specifically constructed as part of the Human Connectome Project. Since that time, numerous technological advances have been made to enable the broader use of the Connectom high gradient system for diffusion tractography and tissue microstructure studies and leverage its unique advantages and sensitivity to resolving macroscopic and microscopic structural information in neural tissue for clinical and neuroscientific studies. The goal of this review article is to summarize the technical developments that have emerged in the last decade to support and promote large-scale and scientific studies of the human brain using the Connectom scanner. We provide a brief historical perspective on the development of Connectom gradient technology and the efforts that led to the installation of three other Connectom 3T MRI scanners worldwide - one in the United Kingdom in Cardiff, Wales, another in continental Europe in Leipzig, Germany, and the latest in Asia in Shanghai, China. We summarize the key developments in gradient hardware and image acquisition technology that have formed the backbone of Connectom-related research efforts, including the rich array of high-sensitivity receiver coils, pulse sequences, image artifact correction strategies and data preprocessing methods needed to optimize the quality of high-gradient strength diffusion MRI data for subsequent analyses. Finally, we review the scientific impact of the Connectom MRI scanner, including advances in diffusion tractography, tissue microstructural imaging, ex vivo validation, and clinical investigations that have been enabled by Connectom technology. We conclude with brief insights into the unique value of strong gradients for diffusion MRI and where the field is headed in the coming years.
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Affiliation(s)
- Qiuyun Fan
- Department of Biomedical Engineering, College of Precision Instruments and Optoelectronics Engineering, Tianjin University, Tianjin, China; Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Cornelius Eichner
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany
| | - Maryam Afzali
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK; Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9JT, UK
| | - Lars Mueller
- Leeds Institute of Cardiovascular and Metabolic Medicine, University of Leeds, Leeds LS2 9JT, UK
| | - Chantal M W Tax
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK; Image Sciences Institute, University Medical Center (UMC) Utrecht, Utrecht, the Netherlands
| | - Mathias Davids
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Computer Assisted Clinical Medicine, Medical Faculty Mannheim, Heidelberg University, Mannheim, Germany
| | - Mirsad Mahmutovic
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Boris Keil
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), Giessen, Germany
| | - Berkin Bilgic
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Kawin Setsompop
- Department of Radiology, Stanford University, Stanford, CA, USA; Department of Electrical Engineering, Stanford University, Stanford, CA, USA
| | - Hong-Hsi Lee
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Qiyuan Tian
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Chiara Maffei
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Gabriel Ramos-Llordén
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Aapo Nummenmaa
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | | | - Anastasia Yendiki
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Yi-Qiao Song
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; John A. Paulson School of Engineering and Applied Sciences, Harvard University, Cambridge, MA USA
| | - Chu-Chung Huang
- Key Laboratory of Brain Functional Genomics (MOE & STCSM), Affiliated Mental Health Center (ECNU), School of Psychology and Cognitive Science, East China Normal University, Shanghai, China; Shanghai Changning Mental Health Center, Shanghai, China
| | - Ching-Po Lin
- Institute of Neuroscience, National Yang Ming Chiao Tung University, Taipei, Taiwan; Institute of Science and Technology for Brain-Inspired Intelligence, Fudan University, Shanghai, China
| | - Nikolaus Weiskopf
- Department of Neurophysics, Max Planck Institute for Human Cognitive and Brain Sciences, Leipzig, Germany; Felix Bloch Institute for Solid State Physics, Faculty of Physics and Earth Sciences, Leipzig University, Leipzig, Germany
| | - Alfred Anwander
- Max Planck Institute for Human Cognitive and Brain Sciences, Department of Neuropsychology, Leipzig, Germany
| | - Derek K Jones
- Cardiff University Brain Research Imaging Centre (CUBRIC), Cardiff University, Cardiff, Wales, UK
| | - Bruce R Rosen
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Lawrence L Wald
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Susie Y Huang
- Athinoula A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Charlestown, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Massachusetts Institute of Technology, Cambridge, MA, USA.
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9
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Caspers S, Axer M, Gräßel D, Amunts K. Additional fiber orientations in the sagittal stratum-noise or anatomical fine structure? Brain Struct Funct 2022; 227:1331-1345. [PMID: 35113243 PMCID: PMC9046345 DOI: 10.1007/s00429-021-02439-w] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2021] [Accepted: 12/08/2021] [Indexed: 01/13/2023]
Abstract
The sagittal stratum is a prominent and macroscopically clearly visible white-matter structure within occipital and parietal lobes with a highly organized structure of parallel fibers running in rostro-caudal direction. Apart from the major tract running through, i.e., the optic radiation, the source and arrangement of other fibers within the sagittal stratum is only partially understood. Recent diffusion imaging studies in-vivo suggest additional minor fiber directions, perpendicular to the major rostro-caudal ones, but the spatial resolution does not allow to resolve them, and to unambiguously distinguish it from noise. Taking this previous evidence as motivation, the present study used 3D polarized light imaging (3D-PLI) for micrometer resolution analysis of nerve fibers in postmortem specimens of a vervet monkey brain. The analysis of coronal occipital and parietal sections revealed that the sagittal stratum consisted of an external and an internal layer, which are joined and crossed by fibers from the surrounding white matter and the tapetum. Fibers from different parietal and occipital regions entered the sagittal stratum in the dorsal, ventral or middle sector, as solid large bundles or as several small fiber aggregations. These patterns were remarkably similar to published results of tracer experiments in macaques. Taking this correspondence as external validation of 3D-PLI enabled translation to the human brain, where a similarly complex fiber architecture within the sagittal stratum could be exemplified in a human hemisphere in our study. We thus argue in favor of a dedicated fiber microstructure within the sagittal stratum as a correlate of the additional fiber directions typically seen in in-vivo diffusion imaging studies.
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Affiliation(s)
- Svenja Caspers
- Institute for Anatomy I, Medical Faculty & University Hospital Düsseldorf, Heinrich-Heine-University Düsseldorf, 40225, Düsseldorf, Germany.
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany.
| | - Markus Axer
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany
| | - David Gräßel
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany
| | - Katrin Amunts
- Institute of Neuroscience and Medicine (INM-1), Research Centre Jülich, 52425, Jülich, Germany
- C. and O. Vogt Institute for Brain Research, Medical Faculty & University Hospital Düsseldorf, Heinrich Heine University Düsseldorf, 40225, Düsseldorf, Germany
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10
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Tendler BC, Hanayik T, Ansorge O, Bangerter-Christensen S, Berns GS, Bertelsen MF, Bryant KL, Foxley S, van den Heuvel MP, Howard AFD, Huszar IN, Khrapitchev AA, Leonte A, Manger PR, Menke RAL, Mollink J, Mortimer D, Pallebage-Gamarallage M, Roumazeilles L, Sallet J, Scholtens LH, Scott C, Smart A, Turner MR, Wang C, Jbabdi S, Mars RB, Miller KL. The Digital Brain Bank, an open access platform for post-mortem imaging datasets. eLife 2022; 11:e73153. [PMID: 35297760 PMCID: PMC9042233 DOI: 10.7554/elife.73153] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 03/17/2022] [Indexed: 11/13/2022] Open
Abstract
Post-mortem magnetic resonance imaging (MRI) provides the opportunity to acquire high-resolution datasets to investigate neuroanatomy and validate the origins of image contrast through microscopy comparisons. We introduce the Digital Brain Bank (open.win.ox.ac.uk/DigitalBrainBank), a data release platform providing open access to curated, multimodal post-mortem neuroimaging datasets. Datasets span three themes-Digital Neuroanatomist: datasets for detailed neuroanatomical investigations; Digital Brain Zoo: datasets for comparative neuroanatomy; and Digital Pathologist: datasets for neuropathology investigations. The first Digital Brain Bank data release includes 21 distinctive whole-brain diffusion MRI datasets for structural connectivity investigations, alongside microscopy and complementary MRI modalities. This includes one of the highest-resolution whole-brain human diffusion MRI datasets ever acquired, whole-brain diffusion MRI in fourteen nonhuman primate species, and one of the largest post-mortem whole-brain cohort imaging studies in neurodegeneration. The Digital Brain Bank is the culmination of our lab's investment into post-mortem MRI methodology and MRI-microscopy analysis techniques. This manuscript provides a detailed overview of our work with post-mortem imaging to date, including the development of diffusion MRI methods to image large post-mortem samples, including whole, human brains. Taken together, the Digital Brain Bank provides cross-scale, cross-species datasets facilitating the incorporation of post-mortem data into neuroimaging studies.
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Affiliation(s)
- Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Taylor Hanayik
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Olaf Ansorge
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Sarah Bangerter-Christensen
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | | | - Mads F Bertelsen
- Centre for Zoo and Wild Animal Health, Copenhagen ZooFrederiksbergDenmark
| | - Katherine L Bryant
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Sean Foxley
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Department of Radiology, University of ChicagoChicagoUnited States
| | - Martijn P van den Heuvel
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
- Department of Child Psychiatry, Amsterdam Neuroscience, Amsterdam UMC, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Amy FD Howard
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Istvan N Huszar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Alexandre A Khrapitchev
- Medical Research Council Oxford Institute for Radiation Oncology, University of OxfordOxfordUnited Kingdom
| | - Anna Leonte
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Paul R Manger
- School of Anatomical Sciences, Faculty of Health Sciences, University of the WitwatersrandJohannesburgSouth Africa
| | - Ricarda AL Menke
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Jeroen Mollink
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Duncan Mortimer
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Menuka Pallebage-Gamarallage
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Lea Roumazeilles
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
| | - Jerome Sallet
- Wellcome Centre for Integrative Neuroimaging, Department of Experimental Psychology, University of OxfordOxfordUnited Kingdom
- Stem Cell and Brain Research Institute, Université Lyon 1, INSERMBronFrance
| | - Lianne H Scholtens
- Department of Complex Trait Genetics, Centre for Neurogenomics and Cognitive Research, Amsterdam Neuroscience, Vrije Universiteit AmsterdamAmsterdamNetherlands
| | - Connor Scott
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Adele Smart
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Martin R Turner
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Division of Clinical Neurology, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Chaoyue Wang
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
| | - Rogier B Mars
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
- Donders Institute for Brain, Cognition and Behaviour, Radboud University NijmegenNijmegenNetherlands
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of OxfordOxfordUnited Kingdom
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11
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Roger C, Lasbleiz A, Guye M, Dutour A, Gaborit B, Ranjeva JP. The Role of the Human Hypothalamus in Food Intake Networks: An MRI Perspective. Front Nutr 2022; 8:760914. [PMID: 35047539 PMCID: PMC8762294 DOI: 10.3389/fnut.2021.760914] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 12/07/2021] [Indexed: 12/12/2022] Open
Abstract
Hypothalamus (HT), this small structure often perceived through the prism of neuroimaging as morphologically and functionally homogeneous, plays a key role in the primitive act of feeding. The current paper aims at reviewing the contribution of magnetic resonance imaging (MRI) in the study of the role of the HT in food intake regulation. It focuses on the different MRI techniques that have been used to describe structurally and functionally the Human HT. The latest advances in HT parcellation as well as perspectives in this field are presented. The value of MRI in the study of eating disorders such as anorexia nervosa (AN) and obesity are also highlighted.
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Affiliation(s)
- Coleen Roger
- Centre de Résonance Magnétique Biologique et Médicale (CRMBM), Centre National de la Recherche Scientifique (CNRS), Université Aix-Marseille, Marseille, France.,Centre d'Exploration Métabolique par Résonance Magnétique (CEMEREM), Assistance Publique-Hôpitaux de Marseille (AP-HM), Hôpital Universitaire de la Timone, Marseille, France
| | - Adèle Lasbleiz
- Centre d'Exploration Métabolique par Résonance Magnétique (CEMEREM), Assistance Publique-Hôpitaux de Marseille (AP-HM), Hôpital Universitaire de la Timone, Marseille, France.,Département d'Endocrinologie, Assistance Publique-Hôpitaux de Marseille (AP-HM), Hôpital de la Conception, Marseille, France
| | - Maxime Guye
- Centre de Résonance Magnétique Biologique et Médicale (CRMBM), Centre National de la Recherche Scientifique (CNRS), Université Aix-Marseille, Marseille, France.,Centre d'Exploration Métabolique par Résonance Magnétique (CEMEREM), Assistance Publique-Hôpitaux de Marseille (AP-HM), Hôpital Universitaire de la Timone, Marseille, France
| | - Anne Dutour
- Département d'Endocrinologie, Assistance Publique-Hôpitaux de Marseille (AP-HM), Hôpital de la Conception, Marseille, France
| | - Bénédicte Gaborit
- Département d'Endocrinologie, Assistance Publique-Hôpitaux de Marseille (AP-HM), Hôpital de la Conception, Marseille, France
| | - Jean-Philippe Ranjeva
- Centre de Résonance Magnétique Biologique et Médicale (CRMBM), Centre National de la Recherche Scientifique (CNRS), Université Aix-Marseille, Marseille, France.,Centre d'Exploration Métabolique par Résonance Magnétique (CEMEREM), Assistance Publique-Hôpitaux de Marseille (AP-HM), Hôpital Universitaire de la Timone, Marseille, France
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12
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Lv Y, Fan Y, Tian X, Yu B, Song C, Feng C, Zhang L, Ji X, Zablotskii V, Zhang X. The Anti-Depressive Effects of Ultra-High Static Magnetic Field. J Magn Reson Imaging 2021; 56:354-365. [PMID: 34921571 DOI: 10.1002/jmri.28035] [Citation(s) in RCA: 11] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Revised: 12/06/2021] [Accepted: 12/08/2021] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND Ultra-high field magnetic resonance imaging (MRI) has obvious advantages in acquiring high-resolution images. 7 T MRI has been clinically approved and 21.1 T MRI has also been tested on rodents. PURPOSE To examine the effects of ultra-high field on mice behavior and neuron activity. STUDY TYPE Prospective, animal model. ANIMAL MODEL Ninety-eight healthy C57BL/6 mice and 18 depression model mice. FIELD STRENGTH 11.1-33.0 T SMF (static magnetic field) for 1 hour and 7 T for 8 hours. Gradients were not on and no imaging sequence was used. ASSESSMENT Open field test, elevated plus maze, three-chambered social test, Morris water maze, tail suspension test, sucrose preference test, blood routine, biochemistry examinations, enzyme-linked immunosorbent assay, immunofluorescent assay. STATISTICAL TESTS The normality of the data was assessed by Shapiro-Wilk test, followed by Student's t test or the Mann-Whitney U test for statistical significance. The statistical cut-off line is P < 0.05. RESULTS Compared to the sham group, healthy C57/6 mice spent more time in the center area (35.12 ± 4.034, increased by 47.19%) in open field test and improved novel index (0.6201 ± 0.02522, increased by 16.76%) in three-chambered social test a few weeks after 1 hour 11.1-33.0 T SMF exposure. 7 T SMF exposure for 8 hours alleviated the depression state of depression mice, including less immobile time in tail suspension test (58.32% reduction) and higher sucrose preference (increased by 8.80%). Brain tissue analysis shows that 11.1-33.0 T and 7 T SMFs can increase oxytocin by 164.65% and 36.03%, respectively. Moreover, the c-Fos level in hippocampus region was increased by 14.79%. DATA CONCLUSION 11.1-33.0 T SMFs exposure for 1 hour or 7 T SMF exposure for 8 hours did not have detrimental effects on healthy or depressed mice. Instead, these ultra-high field SMFs have anti-depressive potentials. EVIDENCE LEVEL 1 TECHNICAL EFFICACY: Stage 1.
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Affiliation(s)
- Yue Lv
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China
| | - Yixiang Fan
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China
| | - Xiaofei Tian
- Institutes of Physical Science and Information Technology, Anhui University, Hefei, China
| | - Biao Yu
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China
| | - Chao Song
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China
| | - Chuanlin Feng
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China
| | - Lei Zhang
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China
| | - Xinmiao Ji
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China
| | - Vitalii Zablotskii
- Institute of Physics, Czech Academy of Sciences, Prague, Czech Republic.,International Magnetobiology Frontier Research Center, Hefei, China
| | - Xin Zhang
- High Magnetic Field Laboratory, Key Laboratory of High Magnetic Field and Ion Beam Physical Biology, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China.,Institutes of Physical Science and Information Technology, Anhui University, Hefei, China.,International Magnetobiology Frontier Research Center, Hefei, China
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13
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Scholz A, Etzel R, May MW, Mahmutovic M, Tian Q, Ramos-Llordén G, Maffei C, Bilgiç B, Witzel T, Stockmann JP, Mekkaoui C, Wald LL, Huang SY, Yendiki A, Keil B. A 48-channel receive array coil for mesoscopic diffusion-weighted MRI of ex vivo human brain on the 3 T connectome scanner. Neuroimage 2021; 238:118256. [PMID: 34118399 PMCID: PMC8439104 DOI: 10.1016/j.neuroimage.2021.118256] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2021] [Revised: 06/04/2021] [Accepted: 06/07/2021] [Indexed: 12/14/2022] Open
Abstract
In vivo diffusion-weighted magnetic resonance imaging is limited in signal-to-noise-ratio (SNR) and acquisition time, which constrains spatial resolution to the macroscale regime. Ex vivo imaging, which allows for arbitrarily long scan times, is critical for exploring human brain structure in the mesoscale regime without loss of SNR. Standard head array coils designed for patients are sub-optimal for imaging ex vivo whole brain specimens. The goal of this work was to design and construct a 48-channel ex vivo whole brain array coil for high-resolution and high b-value diffusion-weighted imaging on a 3T Connectome scanner. The coil was validated with bench measurements and characterized by imaging metrics on an agar brain phantom and an ex vivo human brain sample. The two-segment coil former was constructed for a close fit to a whole human brain, with small receive elements distributed over the entire brain. Imaging tests including SNR and G-factor maps were compared to a 64-channel head coil designed for in vivo use. There was a 2.9-fold increase in SNR in the peripheral cortex and a 1.3-fold gain in the center when compared to the 64-channel head coil. The 48-channel ex vivo whole brain coil also decreases noise amplification in highly parallel imaging, allowing acceleration factors of approximately one unit higher for a given noise amplification level. The acquired diffusion-weighted images in a whole ex vivo brain specimen demonstrate the applicability and advantage of the developed coil for high-resolution and high b-value diffusion-weighted ex vivo brain MRI studies.
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Affiliation(s)
- Alina Scholz
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany.
| | - Robin Etzel
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany
| | - Markus W May
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany
| | - Mirsad Mahmutovic
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany
| | - Qiyuan Tian
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Gabriel Ramos-Llordén
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Chiara Maffei
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Berkin Bilgiç
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Thomas Witzel
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Jason P Stockmann
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Choukri Mekkaoui
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Lawrence L Wald
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Susie Yi Huang
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA; Harvard-MIT Division of Health Sciences and Technology, Cambridge, MA, USA
| | - Anastasia Yendiki
- A.A. Martinos Center for Biomedical Imaging, Department of Radiology, Massachusetts General Hospital, Boston, MA, USA; Harvard Medical School, Boston, MA, USA
| | - Boris Keil
- Institute of Medical Physics and Radiation Protection (IMPS), TH-Mittelhessen University of Applied Sciences (THM), 14 Wiesenstrasse, Giessen 35390, Germany; Center for Mind, Brain and Behavior (CMBB), Marburg, Germany
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14
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Lechanoine F, Jacquesson T, Beaujoin J, Serres B, Mohammadi M, Planty-Bonjour A, Andersson F, Poupon F, Poupon C, Destrieux C. WIKIBrainStem: An online atlas to manually segment the human brainstem at the mesoscopic scale from ultrahigh field MRI. Neuroimage 2021; 236:118080. [PMID: 33882348 DOI: 10.1016/j.neuroimage.2021.118080] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 03/30/2021] [Accepted: 04/08/2021] [Indexed: 01/03/2023] Open
Abstract
The brainstem is one of the most densely packed areas of the central nervous system in terms of gray, but also white, matter structures and, therefore, is a highly functional hub. It has mainly been studied by the means of histological techniques, which requires several hundreds of slices with a loss of the 3D coherence of the whole specimen. Access to the inner structure of the brainstem is possible using Magnetic Resonance Imaging (MRI), but this method has a limited spatial resolution and contrast in vivo. Here, we scanned an ex vivo specimen using an ultra-high field (11.7T) preclinical MRI scanner providing data at a mesoscopic scale for anatomical T2-weighted (100 µm and 185 µm isotropic) and diffusion-weighted imaging (300 µm isotropic). We then proposed a hierarchical segmentation of the inner gray matter of the brainstem and defined a set of rules for each segmented anatomical class. These rules were gathered in a freely accessible web-based application, WIKIBrainStem (https://fibratlas.univ-tours.fr/brainstems/index.html), for 99 structures, from which 13 were subdivided into 29 substructures. This segmentation is, to date, the most detailed one developed from ex vivo MRI of the brainstem. This should be regarded as a tool that will be complemented by future results of alternative methods, such as Optical Coherence Tomography, Polarized Light Imaging or histology… This is a mandatory step prior to segmenting multiple specimens, which will be used to create a probabilistic automated segmentation method of ex vivo, but also in vivo, brainstem and may be used for targeting anatomical structures of interest in managing some degenerative or psychiatric disorders.
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Affiliation(s)
- François Lechanoine
- UMR 1253, iBrain, Université de Tours, Inserm, Tours, France; CHRU de Tours, Tours, France
| | - Timothée Jacquesson
- CREATIS Laboratory CNRS UMR5220, Inserm U1206, INSA-Lyon, University of Lyon 1, Lyon, France
| | | | - Barthélemy Serres
- ILIAD3, Université de Tours, Tours, France; LIFAT, EA6300, Université de Tours, Tours, France
| | | | - Alexia Planty-Bonjour
- UMR 1253, iBrain, Université de Tours, Inserm, Tours, France; CHRU de Tours, Tours, France
| | | | | | - Cyril Poupon
- BAOBAB, Paris-Saclay University, CNRS, CEA, France
| | - Christophe Destrieux
- UMR 1253, iBrain, Université de Tours, Inserm, Tours, France; CHRU de Tours, Tours, France.
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15
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Boonstra JT, Michielse S, Roebroeck A, Temel Y, Jahanshahi A. Dedicated container for postmortem human brain ultra-high field magnetic resonance imaging. Neuroimage 2021; 235:118010. [PMID: 33819610 DOI: 10.1016/j.neuroimage.2021.118010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/06/2020] [Revised: 03/14/2021] [Accepted: 03/23/2021] [Indexed: 11/28/2022] Open
Abstract
BACKGROUND The emerging field of ultra-high field MRI (UHF-MRI, 7 Tesla and higher) provides the opportunity to image human brains at a higher resolution and with higher signal-to-noise ratios compared to the more widely available 1.5 and 3T scanners. Scanning postmortem tissue additionally allows for greatly increased scan times and fewer movement issues leading to improvements in image quality. However, typical postmortem neuroimaging routines involve placing the tissue within plastic bags that leave room for susceptibility artifacts from tissue-air interfaces, inadequate submersion, and leakage issues. To address these challenges in postmortem imaging, a custom-built nonferromagnetic container was developed that allows whole brain hemispheres to be scanned at sub-millimeter resolution within typical head-coils. METHOD The custom-built polymethylmethacrylaat container consists of a cylinder with a hemispheric side and a lid with valves on the adjacent side. This shape fits within common MR head-coils and allows whole hemispheres to be submerged and vacuum sealed within it reducing imaging artifacts that would otherwise arise at air-tissue boundaries. Two hemisphere samples were scanned on a Siemens 9.4T Magnetom MRI scanner. High resolution T2* weighted data was obtained with a custom 3D gradient echo (GRE) sequence and diffusion-weighted imaging (DWI) scans were obtained with a 3D kT-dSTEAM sequence along 48 directions. RESULTS The custom-built container proved to submerge and contain tissue samples effectively and showed no interferences with MR scanning acquisition. The 3D GRE sequence provided high resolution isotropic T2* weighted data at 250 μm which showed a clear visualization of gray and white matter structures. DWI scans allowed for dense reconstruction of structural white matter connections via tractography. CONCLUSION Using this custom-built container worked towards achieving high quality MR images of postmortem brain material. This procedure can have advantages over traditional schemes including utilization of a standardized protocol and the reduced likelihood of leakage. This methodology could be adjusted and used to improve typical postmortem imaging routines.
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Affiliation(s)
- Jackson Tyler Boonstra
- Department of Neurosurgery, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6202 AZ, the Netherlands; School for Mental Health and Neuroscience (MHeNS), Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6200 MD, the Netherlands.
| | - Stijn Michielse
- Department of Neurosurgery, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6202 AZ, the Netherlands; School for Mental Health and Neuroscience (MHeNS), Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6200 MD, the Netherlands
| | - Alard Roebroeck
- Department of Cognitive Neuroscience, Faculty of Psychology & Neuroscience, Maastricht University, the Netherlands
| | - Yasin Temel
- Department of Neurosurgery, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6202 AZ, the Netherlands; School for Mental Health and Neuroscience (MHeNS), Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6200 MD, the Netherlands
| | - Ali Jahanshahi
- Department of Neurosurgery, Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6202 AZ, the Netherlands; School for Mental Health and Neuroscience (MHeNS), Maastricht University Medical Center, P. Debyelaan 25, Maastricht, 6200 MD, the Netherlands
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16
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Tian X, Lv Y, Fan Y, Wang Z, Yu B, Song C, Lu Q, Xi C, Pi L, Zhang X. Safety evaluation of mice exposed to 7.0-33.0 T high-static magnetic fields. J Magn Reson Imaging 2020; 53:1872-1884. [PMID: 33382516 DOI: 10.1002/jmri.27496] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2020] [Revised: 12/14/2020] [Accepted: 12/16/2020] [Indexed: 01/26/2023] Open
Abstract
Magnetic resonance imaging (MRI) of 7 T and higher can provide superior image resolution and capability. Clinical tests have been performed in 9.4 T MRI, and 21.1 T small-bore-size MRI has also been tested in rodents. Although the safety issue is a prerequisite for their future medical application, there are very few relevant studies for the safety of static magnetic fields (SMFs) of ≧20 T. The aim of this study was to assess the biological effects of 7.0-33.0 T SMFs in healthy adult mice. This was a prospective study, in which 104 healthy adult C57BL/6 mice were divided into control, sham control, and 7.0-33.0 T SMF-exposed groups.The sham control group and SMF group were handled identically, except for the electric current for producing SMF. A separate control group was placed outside the magnet and their data were used as normal range. After 1 h exposure, all mice were routinely fed for another 2 months while their body weight and food/water consumption were monitored. After 2 months, their complete blood count, blood biochemistry, key organ weight, and histomorphology were examined. All data are normally distributed. Differences between the sham and SMF-exposed groups were evaluated by unpaired t test. Most indicators did not show statistically significant changes or were still within the normal ranges, with only a few exceptions. For example, mono % in Group 2 (11.1 T) is 6.03 ± 1.43% while the normal range is 6.60-9.90% (p < 0.05). The cholesterol level in 33 T group is 3.38 ± 0.36 mmol/L while the normal range is 2.48-3.29 mmol/L (p < 0.05). The high-density lipoprotein cholesterol level in 33 T group is 2.54 ± 0.29 mmol/L while the normal reference range is 1.89-2.43 mmol/L (p < 0.01). Exposure to 7.0-33.0 T for 1 h did not have detrimental effects on normal adult mice. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY STAGE: 1.
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Affiliation(s)
- Xiaofei Tian
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Institutes of Physical Science and Information Technology, Anhui University, Hefei, China
| | - Yue Lv
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China
| | - Yixiang Fan
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China
| | - Ze Wang
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Hefei National Laboratory for Physical Sciences at Microscale, University of Science and Technology of China, Hefei, China
| | - Biao Yu
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China
| | - Chao Song
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China
| | - Qingyou Lu
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Hefei National Laboratory for Physical Sciences at Microscale, University of Science and Technology of China, Hefei, China.,Anhui Province Key Laboratory of Condensed Matter Physics at Extreme Conditions, Hefei, China
| | - Chuanying Xi
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China
| | - Li Pi
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China
| | - Xin Zhang
- High Magnetic Field Laboratory, Hefei Institutes of Physical Science, Chinese Academy of Sciences, Hefei, China.,Science Island Branch of Graduate School, University of Science and Technology of China, Hefei, China.,Institutes of Physical Science and Information Technology, Anhui University, Hefei, China
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17
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Kim S, Sakaie K, Blümcke I, Jones S, Lowe MJ. Whole-brain, ultra-high spatial resolution ex vivo MRI with off-the-shelf components. Magn Reson Imaging 2020; 76:39-48. [PMID: 33197550 DOI: 10.1016/j.mri.2020.11.002] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2020] [Revised: 10/09/2020] [Accepted: 11/09/2020] [Indexed: 10/23/2022]
Abstract
BACKGROUND Ultra-high spatial resolution imaging of whole, ex vivo brains provides new opportunities to understand neurological disease. Recent work has demonstrated that 100 μm isotropic resolution can reveal anatomical details that are otherwise difficult to appreciate, but relied on fabrication facilities, fabrication expertise and programming expertise that is not available at clinical imaging sites that lack a dedicated research staff and resources. The purpose of this work is to describe a whole-brain, ultra-high spatial resolution imaging procedure for ex vivo specimens using equipment that can be purchased, assembled and implemented by most clinical sites. We provide enough detail so that other groups can readily reproduce the approach. METHODS A container and hardware for holding the brain fixed for long scan times was developed, along with a procedure for removing bubbles, which can cause artifact. Imaging was performed on a standard knee coil on a whole-body 7 T MRI at 170 μm isotropic spatial resolution. Five specimens were examined in Fomblin or formalin to evaluate consistency of image quality. RESULTS High quality images were acquired on all specimens. Anatomical features that are not readily observed at standard resolution, such as subthalamic nuclei, are readily observed. Disease-related features such as microscopic infarcts are also readily observed. CONCLUSIONS Ultra-high spatial resolution, whole-brain images can be readily achieved without specialized hardware and software development. The approach is expected to be valuable as a complement to histology and to discover relationships among pathology located at different places throughout the brain.
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Affiliation(s)
- Sanghoon Kim
- Imaging Institute, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-15, Cleveland, OH 44195, USA
| | - Ken Sakaie
- Imaging Institute, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-15, Cleveland, OH 44195, USA
| | - Ingmar Blümcke
- Institute of Neuropathology, Universitätsklinikum Erlangen, Schwabachanlage 6 (Kopfkliniken), 91054 Erlangen, Germany
| | - Stephen Jones
- Imaging Institute, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-15, Cleveland, OH 44195, USA
| | - Mark J Lowe
- Imaging Institute, The Cleveland Clinic, 9500 Euclid Ave, Mail code U-15, Cleveland, OH 44195, USA.
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18
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Tendler BC, Foxley S, Hernandez-Fernandez M, Cottaar M, Scott C, Ansorge O, Miller KL, Jbabdi S. Use of multi-flip angle measurements to account for transmit inhomogeneity and non-Gaussian diffusion in DW-SSFP. Neuroimage 2020; 220:117113. [PMID: 32621975 PMCID: PMC7573656 DOI: 10.1016/j.neuroimage.2020.117113] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/29/2019] [Revised: 06/25/2020] [Accepted: 06/27/2020] [Indexed: 11/06/2022] Open
Abstract
Diffusion-weighted steady-state free precession (DW-SSFP) is an SNR-efficient diffusion imaging method. The improved SNR and resolution available at ultra-high field has motivated its use at 7T. However, these data tend to have severe B1 inhomogeneity, leading not only to spatially varying SNR, but also to spatially varying diffusivity estimates, confounding comparisons both between and within datasets. This study proposes the acquisition of DW-SSFP data at two-flip angles in combination with explicit modelling of non-Gaussian diffusion to address B1 inhomogeneity at 7T. Data were acquired from five fixed whole human post-mortem brains with a pair of flip angles that jointly optimize the diffusion contrast-to-noise (CNR) across the brain. We compared one- and two-flip angle DW-SSFP data using a tensor model that incorporates the full DW-SSFP Buxton signal, in addition to tractography performed over the cingulum bundle and pre-frontal cortex using a ball & sticks model. The two-flip angle DW-SSFP data produced angular uncertainty and tractography estimates close to the CNR optimal regions in the single-flip angle datasets. The two-flip angle tensor estimates were subsequently fitted using a modified DW-SSFP signal model that incorporates a gamma distribution of diffusivities. This allowed us to generate tensor maps at a single effective b-value yielding more consistent SNR across tissue, in addition to eliminating the B1 dependence on diffusion coefficients and orientation maps. Our proposed approach will allow the use of DW-SSFP at 7T to derive diffusivity estimates that have greater interpretability, both within a single dataset and between experiments.
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Affiliation(s)
- Benjamin C Tendler
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK.
| | - Sean Foxley
- Department of Radiology, University of Chicago, Chicago, IL, USA
| | | | - Michiel Cottaar
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Connor Scott
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Olaf Ansorge
- Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Karla L Miller
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
| | - Saad Jbabdi
- Wellcome Centre for Integrative Neuroimaging, FMRIB, Nuffield Department of Clinical Neurosciences, University of Oxford, Oxford, UK
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19
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Abstract
Whole brain dynamics intuitively depend upon the internal wiring of the brain; but to which extent the individual structural connectome constrains the corresponding functional connectome is unknown, even though its importance is uncontested. After acquiring structural data from individual mice, we virtualized their brain networks and simulated in silico functional MRI data. Theoretical results were validated against empirical awake functional MRI data obtained from the same mice. We demonstrate that individual structural connectomes predict the functional organization of individual brains. Using a virtual mouse brain derived from the Allen Mouse Brain Connectivity Atlas, we further show that the dominant predictors of individual structure-function relations are the asymmetry and the weights of the structural links. Model predictions were validated experimentally using tracer injections, identifying which missing connections (not measurable with diffusion MRI) are important for whole brain dynamics in the mouse. Individual variations thus define a specific structural fingerprint with direct impact upon the functional organization of individual brains, a key feature for personalized medicine.
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